True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries

Autor: Carine Van Malderen, Dejan Zurovac, Dieter Vanderelst, Elvire Mfueni, Léon Tshilolo, Angel Rosas-Aguirre, Bernhards Ogutu, Brecht Devleesschauwer, Robert W. Snow, Niko Speybroeck, Patrick T. Brandt
Jazyk: angličtina
Rok vydání: 2018
Předmět:
AFRICA
medicine.medical_specialty
lcsh:Arctic medicine. Tropical medicine
lcsh:RC955-962
030231 tropical medicine
Prevalence
DISEASE PREVALENCE
True prevalence
RAPID DIAGNOSTIC-TEST
Bayesian data analysis
lcsh:Infectious and parasitic diseases
03 medical and health sciences
0302 clinical medicine
Environmental health
parasitic diseases
medicine
Medicine and Health Sciences
Humans
lcsh:RC109-216
030212 general & internal medicine
Africa South of the Sahara
Retrospective Studies
Estimation
Rapid diagnostic test
Conditional dependence
Under-five
PLASMODIUM-FALCIPARUM
Sub-Saharan Africa
business.industry
Public health
Research
Infant
Bayes Theorem
MICROSCOPY
Gold standard (test)
GOLD STANDARD
medicine.disease
3. Good health
Malaria
Infectious Diseases
Mathematics and Statistics
PCR
Child
Preschool
TESTS
Parasitology
business
KENYA
Zdroj: Malaria Journal, Vol 17, Iss 1, Pp 1-7 (2018)
MALARIA JOURNAL
Malaria Journal
ISSN: 1475-2875
DOI: 10.1186/s12936-018-2211-y
Popis: Background Malaria is one of the major causes of childhood death in sub-Saharan countries. A reliable estimation of malaria prevalence is important to guide and monitor progress toward control and elimination. The aim of the study was to estimate the true prevalence of malaria in children under five in the Democratic Republic of the Congo, Uganda and Kenya, using a Bayesian modelling framework that combined in a novel way malaria data from national household surveys with external information about the sensitivity and specificity of the malaria diagnostic methods used in those surveys—i.e., rapid diagnostic tests and light microscopy. Methods Data were used from the Demographic and Health Surveys (DHS) and Malaria Indicator Surveys (MIS) conducted in the Democratic Republic of the Congo (DHS 2013–2014), Uganda (MIS 2014–2015) and Kenya (MIS 2015), where information on infection status using rapid diagnostic tests and/or light microscopy was available for 13,573 children. True prevalence was estimated using a Bayesian model that accounted for the conditional dependence between the two diagnostic methods, and the uncertainty of their sensitivities and specificities obtained from expert opinion. Results The estimated true malaria prevalence was 20% (95% uncertainty interval [UI] 17%–23%) in the Democratic Republic of the Congo, 22% (95% UI 9–32%) in Uganda and 1% (95% UI 0–3%) in Kenya. According to the model estimations, rapid diagnostic tests had a satisfactory sensitivity and specificity, and light microscopy had a variable sensitivity, but a satisfactory specificity. Adding reported history of fever in the previous 14 days as a third diagnostic method to the model did not affect model estimates, highlighting the poor performance of this indicator as a malaria diagnostic. Conclusions In the absence of a gold standard test, Bayesian models can assist in the optimal estimation of the malaria burden, using individual results from several tests and expert opinion about the performance of those tests. Electronic supplementary material The online version of this article (10.1186/s12936-018-2211-y) contains supplementary material, which is available to authorized users.
Databáze: OpenAIRE
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